Adaptive SMO-Based Fault Estimation for Markov Jump Systems With Simultaneous Additive and Multiplicative Actuator Faults
Hongyan Yang, Hao Luo, Okyay Kaynak, Shen Yin
Abstract
This article studies the problem of fault reconstruction, disturbance estimation, and state estimation for Markovian jump systems (MJSs) with simultaneous additive and multiplicative actuator faults. First, we rewrite the original Markov jump linear systems into an extended form, where the extended vector is composed of an actuator fault vector, a disturbance vector, and a state vector. Then, by proposing a continuous adaptive sliding-mode observer for the extended-form MJSs, the state estimation, actuator fault reconstruction, and disturbance estimation can be achieved. Moreover, the stochastic stability of the overall error plant can be guaranteed. Finally, a simulation example is employed to illustrate the effectiveness of our theoretical results.